GHSA-RRC7-8W2H-XW89

Vulnerability from github – Published: 2024-08-12 15:30 – Updated: 2026-10-30 18:32
VLAI
Details

A vulnerability was found in OpenShift AI that allows for authentication bypass and privilege escalation across models within the same namespace. When deploying AI models, the UI provides the option to protect models with authentication. However, credentials from one model can be used to access other models and APIs within the same namespace. The exposed ServiceAccount tokens, visible in the UI, can be utilized with oc --token={token} to exploit the elevated view privileges associated with the ServiceAccount, leading to unauthorized access to additional resources.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2024-7557"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-284",
      "CWE-305"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-08-12T13:38:43Z",
    "severity": "HIGH"
  },
  "details": "A vulnerability was found in OpenShift AI that allows for authentication bypass and privilege escalation across models within the same namespace. When deploying AI models, the UI provides the option to protect models with authentication. However, credentials from one model can be used to access other models and APIs within the same namespace. The exposed ServiceAccount tokens, visible in the UI, can be utilized with oc --token={token} to exploit the elevated view privileges associated with the ServiceAccount, leading to unauthorized access to additional resources.",
  "id": "GHSA-rrc7-8w2h-xw89",
  "modified": "2026-10-30T18:32:14Z",
  "published": "2024-08-12T15:30:52Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-7557"
    },
    {
      "type": "WEB",
      "url": "https://github.com/opendatahub-io/odh-dashboard/pull/3198"
    },
    {
      "type": "WEB",
      "url": "https://access.redhat.com/errata/RHBA-2024:8240"
    },
    {
      "type": "WEB",
      "url": "https://access.redhat.com/security/cve/CVE-2024-7557"
    },
    {
      "type": "WEB",
      "url": "https://bugzilla.redhat.com/show_bug.cgi?id=2303094"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:A/AC:L/PR:L/UI:N/S:C/C:H/I:L/A:N",
      "type": "CVSS_V3"
    }
  ]
}



Log in or create an account to share your comment.




Tags
Taxonomy of the tags.


Loading…

Loading…

Loading…

Drag nodes to arrange them. Double-click a related vulnerability to open it, or a source to visit its link. The Physics button on the left tunes the layout and the simulation; the legend at the bottom left hides or shows nodes by kind and by sighting type.

Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.

Sightings

Author Source Type Date Other

Nomenclature

  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
  • Confirmed: The vulnerability has been validated from an analyst's perspective.
  • Published Proof of Concept: A public proof of concept is available for this vulnerability.
  • Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
  • Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
  • Not confirmed: The user expressed doubt about the validity of the vulnerability.
  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
Vulnerability timeline

Sightings and recorded dates, grouped by day · UTC

JSON
Events included in the timeline

Loading timeline…


    Loading…

    Loading…

    Loading…

    Related by attack behaviour

    Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.